Cientista Dados Aplicados

Syngenta; São Paulo; Presencial; BRL 80.000 - 120.000; Tempo integral

Resumo da oferta

A leading company in seed development seeks a Data Scientist to enhance agricultural product development. The ideal candidate will leverage data science to improve plant breeding and environmental modeling, collaborating across teams to deliver actionable insights. This role requires strong technical skills in Python, R, and cloud platforms, along with the ability to communicate effectively with both technical and non-technical stakeholders.

Qualificações

• Bachelor’s degree in agronomy, statistics, or related fields.
• Master’s or PhD preferred in genetics, quantitative genetics, or data science.

Responsabilidades

• Develop and implement global environmental modeling tools.
• Collaborate with stakeholders to drive data-driven strategies.
• Translate complex business questions into data science problems.

Conhecimentos

Proactive

Autonomous

Goal Oriented

Communication

Formação académica

Bachelor’s degree in agronomy

Master’s or PhD in genetics

Ferramentas

Python

R

AWS

Azure

GCP

Power BI

Tableau

Qlik Sense

Git

Descrição da oferta de emprego

Company Description

Syngenta Seeds is one of the world's largest seed developers and producers for farmers, commercial growers, retailers and small seed companies. Syngenta seeds improve crop quality and yield. High quality seeds ensure better and more productive crops, which is why farmers invest in them. Advanced seeds help mitigate risks such as disease and drought and allow farmers to grow food using less land, less water and fewer inputs.

Syngenta Seeds brings growers more vigorous, strong and resilient plants, including innovative hybrid varieties and biotech crops that can thrive even in challenging growing conditions.

Syngenta Seeds is based in the United States.

Job Description

Job title: Data scientist (São Paulo or Uberlândia)

Scope: Product Development Global

We are looking for a highly skilled and proactive scientist with solid experience in data science applied to the agriculture sector, especially in plant breeding, genomic prediction, environmental modelling, and product advancement and placement. The ideal candidate is not only technically strong, but also business-driven, capable of translating business needs into analytical solutions, and communicating results in a clear and actionable way to both technical and non-technical stakeholders.

The Data Scientist will play a strategic role in identifying high-impact opportunities, prioritizing projects based on value and feasibility, and ensuring the successful communication and delivery of data science outcomes across the organization.

• Participation in the development and implementation of global environmental characterization and modeling tools to support product advancement and placement
• Collaborate with regional business and technical stakeholders to drive a data and insight-driven trialing network and product placement strategy
• Knowledge transfer across technical teams, increasing data science fluency within the organization
• Data visualizations to deliver your results and drive business insights, using dashboards and visual analytics tools, such as Power BI, Tableau, R-Shiny, or Qlik Sense.
• Cloud-native model deployment using services such as AWS SageMaker, Azure ML, or GCP Vertex AI.
• Well-documented APIs and microservices for consumption and integration of machine learning outputs.
• Clear technical documentation and reproducible workflows to support research and cross-team collaboration.
• Performance reports and continuous improvement recommendations based on model evaluation and business feedback.
• Effective business storytelling: translate complex analytical results into strategic insights for leadership and functional teams.
• Project impact evaluations to prioritize initiatives and allocate resources efficiently.

• Translate complex business questions into data science problems, delivering actionable insights and measurable results.
• Collaborate with agronomists, breeders, data scientists, product managers, and tech teams to define project goals and success metrics.
• Evaluate project feasibility and business impact, providing input for prioritization and strategic decision-making.
• Ensure transparent communication of deliverables and timelines, aligning with business stakeholders and leadership.
• Foster a collaborative, insight-driven culture, bridging the gap between technical and functional areas.

Qualifications

Education:

• Bachelor’s degree in agronomy, statistics, biotechnology, science and technology, computer science, computer engineering, or related fields.
• Master’s or PhD (preferred) in genetics, quantitative genetics, plant breeding, statistics, bioinformatics, data science or another relevant scientific field.

Technical Skills:

• Solid experience in at least one of the following: environmental modelling, machine learning for environmental prediction, quantitative genetics, linear mixed models.
• Proficient in Python and/or R, experience in ML frameworks is desired. Software version control and best practices using Git is a must.
• Solid understanding of SQL/NoSQL databases and data engineering principles
• Hands-on experience with cloud platforms (AWS, Azure, GCP)
• Experience using of visualization tools: R Shiny, Power BI, Tableau, Qlik Sense.

Soft Skills & Business Acumen:

• Highly proactive, autonomous, and goal oriented.
• Ability to translate technical results into strategic business insights.
• Skilled in communicating with leadership and cross-functional teams
• Capable of assessing project value and impact to drive prioritization
• Comfortable working in fast-paced, multidisciplinary environments

Nice to have:

• Experience in agtech, biotech, or agricultural research environments
• Publications, patents, or scientific contributions in related areas

Additional Information

Beyond just believing in the power of diversity, Syngenta promotes an inclusive culture that includes differences in all its forms. We believe that the feeling of belonging allows people to become their best version, building an increasingly welcoming and productive environment.

All qualified candidates will be considered for our positions, without distinction of race, gender, age, nationality, or disability.

WL 4B